DAPRO adaptively spends a fixed interaction budget across multi-turn LLM conversations and builds valid lower bounds on time-to-jailbreak, with coverage error scaling as the square root of the mean censoring weight.
Cer-eval: Certifiable and cost-efficient evaluation framework for llms
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Bayesian deep learning method rankings are unreliable under data scarcity, reversing across datasets and sample sizes, and a hierarchical Bayesian framework with predictive detectability curves is needed to assess evaluation sufficiency.
citing papers explorer
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How Many Iterations to Jailbreak? Dynamic Budget Allocation for Multi-Turn LLM Evaluation
DAPRO adaptively spends a fixed interaction budget across multi-turn LLM conversations and builds valid lower bounds on time-to-jailbreak, with coverage error scaling as the square root of the mean censoring weight.
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ProEval: Proactive Failure Discovery and Efficient Performance Estimation for Generative AI Evaluation
Bayesian deep learning method rankings are unreliable under data scarcity, reversing across datasets and sample sizes, and a hierarchical Bayesian framework with predictive detectability curves is needed to assess evaluation sufficiency.